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Article Dans Une Revue Journal of Mathematical Imaging and Vision Année : 2015

Inf-structuring Functions: A Unifying Theory of Connections and Connected Operators

Résumé

During the last decade, several theories have been proposed in order to extend the notion of set connections in mathematical morphology. These new theories were obtained by generalizing the definition to wider spaces (namely complete lattices) and/or by relaxing some hypothesis. Nevertheless, the links among those different theories are not always well understood, and this work aims at defining a unifying theoretical framework. The adopted approach relies on the notion of inf-structuring function which is simply a mapping that associates a set of sub-elements to each element of the space. The developed theory focuses on the properties of the decompositions given by an inf-structuring function rather than in trying to characterize the properties of the set of connected elements as a whole. We establish several sets of inf-structuring function properties that enable to recover the existing notions of connections, hyperconnections, and attribute space connections. Moreover, we also study the case of grey-scale connected operators that are obtained by stacking set connected operators and we show that they can be obtained using specific inf-structuring functions. This work allows us to better understand the existing theories, it facilitates the reuse of existing results among the different theories and it gives a better view on the unexplored areas of the connection theories.
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Dates et versions

hal-01018791 , version 1 (05-07-2014)

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Benjamin Perret. Inf-structuring Functions: A Unifying Theory of Connections and Connected Operators. Journal of Mathematical Imaging and Vision, 2015, 51 (1), pp.171-194. ⟨10.1007/s10851-014-0515-2⟩. ⟨hal-01018791⟩
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